DEV Community: Jasper Smith

I Built an AI Video Generator with Next.js and Got My First Paid User in 3 Months

Jasper Smith — Sat, 25 Jul 2026 16:56:57 +0000

I Built an AI Video Generator with Next.js and Got My First Paid User in 3 Months

I'm a frontend developer working at a bank in Shenzhen. By day I write React components. By night, I've been building Froging AI — an AI video generator that turns images and text into videos in minutes.

Three months ago I knew nothing about AI video APIs. Last week, I got my first paid order. Here’s how it happened.

The Stack

I wanted to ship fast and keep costs low. My stack:

Next.js 14 (App Router) — frontend + API routes in one repo
Supabase — Auth, PostgreSQL, and storage
Vercel — deployment, zero DevOps
Creem — payments (one-time + subscriptions)
Replicate / Minimax / 海螺AI — video generation APIs

Why not Python? I'm a frontend dev. Next.js API routes handle async queueing just fine. I didn't want to learn a new deployment pipeline. Ship fast, iterate faster.

What It Does

Froging AI has two core features:

Image to Video
Upload a photo, add a prompt, and the AI animates it into a short video clip. Good for product demos, social content, and creative experiments.

Text to Video
Describe a scene in plain English and get a generated video back in minutes. No camera, no editing software.

Under the hood, I'm routing requests to different providers based on model availability and cost. Replicate's open-source models (Wan-2.1, etc.) for cheap experiments. Minimax and 海螺AI for higher-quality outputs. The user doesn’t pick the model — the system optimizes for speed and quality automatically.

The First Dollar

On July 13th, I woke up to an email from Creem: "You received a payment."

It was $4.99. One user bought the Starter plan.

That small amount changed everything. Before that, I was optimizing SEO, tweaking landing page colors, and watching Google Analytics like a hawk. After that, I realized: the only metric that matters is whether someone is willing to pay.

The user came from organic search. I had spent weeks writing blog posts, submitting to AI directories, and building backlinks. No ads. Just content and patience.

3 Things I Learned

1. Start with one feature, not ten

My original plan was an "all-in-one AI creative suite" — image generation, video generation, editing tools, the works. I stripped it down to video only. If I had waited for the full vision, I'd still be coding instead of charging.

2. SEO is a patience game

I stopped Google Ads after burning through budget with zero conversions. Switched to long-tail SEO: "image to video AI free", "text to video generator no signup". Slow traffic, but free and compounding.

3. Payment integration is part of the product

I spent too much time perfecting the UI before integrating Creem. The moment payments went live, my mindset shifted from "hobby project" to "business." Do it early. Even if nobody pays, the infrastructure being ready changes how you build.

What's Next

Image generation is on the roadmap (finally expanding beyond video)
Better mobile experience (most traffic is mobile)
More video models — I'm watching Kling 2.6 and Veo-3 closely

Try It

If you're curious, Froging AI is live. You can generate a few videos for free without signing up.

If you're also building a side project, drop a comment. I read every one.

Tags: #ai #webdev #nextjs #saas #sideproject #startup #indiedev

Building an AI Image Detector with Next.js: Lessons from Shipping Fast

Jasper Smith — Tue, 30 Jun 2026 16:13:44 +0000

I recently shipped AI Picture Checker — a free online AI Image Detector that identifies whether a photo was generated by AI and, more importantly, which model created it (Midjourney, DALL·E, Gemini, Flux, etc.).

Here is what I learned from building and launching it in under two weeks.

The Problem

Most AI image detectors give you a vague "AI vs Real" percentage. That is fine for curiosity, but useless when you are moderating user uploads or verifying a news photo. You need to know:

Is this actually synthetic?
Which generator was used?
Is it a deepfake or a fully generated image?

Existing tools either hide results behind paywalls or require accounts before you can even test them.

The Stack

Next.js 14 (App Router) + TypeScript
Supabase — Auth, Postgres, and file storage
Vercel — Edge functions and global CDN
Detection models — Ensemble of Hive AI API + custom CLIP-based classifier
Sharp — Client-side image preprocessing before upload

One Technical Lesson

Do not trust a single model.

During testing, one commercial API scored 96% accuracy on Midjourney v6 images but dropped to 62% on Gemini-generated photos. Inpainted images (real photo + AI-edited regions) fooled it completely.

The fix was an ensemble approach:

Run multiple detectors in parallel
Weight scores by model confidence
Fall back to metadata checks (C2PA signatures) when available

This pushed the blended accuracy above 90% across the board, though it increased the per-request cost to roughly $0.005–$0.008.

The SEO Play

I launched the landing page before the detection API was fully integrated. Why? To start indexing immediately.

I published a dozen blog posts targeting long-tail keywords — AI Image Detector, AI Picture Checker, check if image is AI generated, deepfake detection online — and pointed internal links to the main tool.

Three months later, organic traffic is the primary growth channel. For solo developers, content-first, feature-second is a viable launch strategy.

Try It

You can check if an image is AI-generated at aipicturechecker.com. No signup is required for the first few checks. Upload a JPG, PNG, or WebP (up to 10MB) and get results in seconds.

If you find an image that fools the detector, drop a link in the comments — I use edge cases like that to retrain the model.

Resources

AI Picture Checker — Free AI Image Detector with source attribution
Hive Moderation — Enterprise detection API
C2PA — Content authenticity standards

Building AI tools at LuTa Tech. Follow for more write-ups on shipping fast, Next.js architecture, and generative media.

Gemini Omni Video Generator: Create Cinematic AI Videos with Veo

Jasper Smith — Sat, 23 May 2026 16:40:27 +0000

Introducing Gemini Omni Video Generator

AI video creation has just taken a massive leap forward. Gemini Omni Video Generator is a powerful AI-powered platform that lets you create stunning cinematic videos from simple text prompts and images — powered by Google's Veo models.

What Can You Create?

Cinematic Videos — Generate high-quality, movie-like scenes from text descriptions
Image-to-Video Animations — Bring your static images to life with fluid motion
Short-Form Social Content — Create engaging clips for Instagram, TikTok, and YouTube Shorts
Marketing Videos — Produce professional promotional content in seconds
Creative Storytelling — Visualize narratives with AI-generated scenes

Why Gemini Omni?

Built on top of Google's Gemini Omni and Veo AI models, this platform delivers:

Fast, professional AI video production
Simple, intuitive workflows
High-quality output with realistic motion
No complex editing skills required

Who Is It For?

Whether you're a content creator, marketer, or part of a content team, Gemini Omni Video Generator streamlines your video production pipeline. No more spending hours on animation — describe what you want, and let AI bring your vision to life.

Get Started

Ready to create your first AI video? Visit geminiomnivideo.io and start generating cinematic content in seconds.

We Built an AI Image-to-Video Generator in 2026: Architecture, Challenges, and Lessons Learned

Jasper Smith — Tue, 07 Apr 2026 13:05:46 +0000

TL;DR

We just launched AI Image to Video, a free tool that transforms static images into professional videos using AI. Built by LuTa Tech, it's designed for developers and creators who need quick, high-quality video content without complex editing workflows.

Try it here 👉 https://www.aiimagetovideo.video/

The Problem

As developers building content tools, we kept hitting the same wall: video creation is hard.

Whether you're building a landing page, creating social media content, or prototyping an app, you need video assets. But traditional video editing requires:

Expensive software (After Effects, Premiere Pro)
Steep learning curves
Hours of manual work

We wanted something as simple as:

Upload an image
Write a prompt ("make the ocean waves move")
Get a video in seconds

So we built it.

The Architecture

Frontend Stack

React + TypeScript - Type safety for complex canvas operations
WebGL/Canvas API - Real-time preview and image processing
Tailwind CSS - Rapid UI development

AI/Backend

Python FastAPI - High-performance async video processing
Diffusion Models - Custom fine-tuned models for motion generation
FFmpeg - Video encoding and optimization
AWS S3 + CloudFront - Asset storage and global CDN delivery

The Tricky Parts

1. Browser-side Image Processing
Handling large images (4K+) in the browser without crashing tabs was challenging. We implemented:

Web Workers for off-main-thread processing
Progressive image loading
Canvas tiling for memory efficiency

2. Prompt Engineering for Motion
Getting AI to understand "how things should move" requires careful prompt structuring. We built a prompt enhancement layer that translates user inputs into model-optimized instructions.

3. Video Encoding in the Cloud
Balancing quality vs. processing time vs. cost. We ended up with a tiered system:

Fast preview (480p, 5s generation)
High quality (1080p, 30s generation)

What We Built

AI Image to Video lets you:

✅ Upload any image (JPG, PNG, WebP)
✅ Describe motion with natural language ("gentle waves", "falling leaves")
✅ Get MP4 output in seconds
✅ Use it for free (with reasonable limits for server costs)

Use cases we've seen:

E-commerce product demos
Social media content creation
Game asset generation
Prototyping video concepts

About LuTa Tech

This project is built by LuTa Tech, a small team focused on making AI creative tools accessible to developers and creators.

We're not trying to replace professional video editors. Instead, we're building the "quick prototype to video" layer that every developer needs in their toolkit.

Check out our other projects at luta-tech.com

Try It & Give Feedback

The tool is live and free to try: https://www.aiimagetovideo.video/

For developers:

We have an API coming soon (join the waitlist on the site)
If you're building something similar, happy to share more technical details in the comments

What's next?

Video-to-video translation
Batch processing API
Open-source some of our preprocessing tools

Drop your thoughts in the comments! What would you use this for?

This post is not sponsored. Just sharing a tool we built that might help fellow developers.